Zobrazeno 1 - 10
of 916
pro vyhledávání: '"A. Siomos"'
Federated learning is a decentralized collaborative training paradigm that preserves stakeholders' data ownership while improving performance and generalization. However, statistical heterogeneity among client datasets poses a fundamental challenge b
Externí odkaz:
http://arxiv.org/abs/2410.02006
Autor:
Marimont, Sergio Naval, Siomos, Vasilis, Baugh, Matthew, Tzelepis, Christos, Kainz, Bernhard, Tarroni, Giacomo
Unsupervised Anomaly Detection (UAD) methods aim to identify anomalies in test samples comparing them with a normative distribution learned from a dataset known to be anomaly-free. Approaches based on generative models offer interpretability by gener
Externí odkaz:
http://arxiv.org/abs/2407.06635
Autor:
Marimont, Sergio Naval, Baugh, Matthew, Siomos, Vasilis, Tzelepis, Christos, Kainz, Bernhard, Tarroni, Giacomo
Unsupervised Anomaly Detection (UAD) techniques aim to identify and localize anomalies without relying on annotations, only leveraging a model trained on a dataset known to be free of anomalies. Diffusion models learn to modify inputs $x$ to increase
Externí odkaz:
http://arxiv.org/abs/2311.15453
Federated Learning (FL) is a collaborative training paradigm that allows for privacy-preserving learning of cross-institutional models by eliminating the exchange of sensitive data and instead relying on the exchange of model parameters between the c
Externí odkaz:
http://arxiv.org/abs/2311.14625
Federated Learning (FL) has seen increasing interest in cases where entities want to collaboratively train models while maintaining privacy and governance over their data. In FL, clients with private and potentially heterogeneous data and compute res
Externí odkaz:
http://arxiv.org/abs/2311.09856
Unsupervised Out-of-Distribution (OOD) detection consists in identifying anomalous regions in images leveraging only models trained on images of healthy anatomy. An established approach is to tokenize images and model the distribution of tokens with
Externí odkaz:
http://arxiv.org/abs/2307.14701
Publikováno v:
Sensors, Vol 24, Iss 23, p 7547 (2024)
The market demand for baby leaf lettuce is constantly increasing, while safety has become one of the most important traits in determining consumer preference driven by human health hazards concerns. In this study, the performance of visible and near-
Externí odkaz:
https://doaj.org/article/a428f17f2b744bcdaa7c6830237cf0e6
Autor:
Delianidi, Marina, Salampasis, Michail, Diamantaras, Konstantinos, Siomos, Theodosios, Katsalis, Alkiviadis, Karaveli, Iphigenia
We present a graph-based approach for the data management tasks and the efficient operation of a system for session-based next-item recommendations. The proposed method can collect data continuously and incrementally from an ecommerce web site, thus
Externí odkaz:
http://arxiv.org/abs/2106.12085
Autor:
Efstratios Androudis, Athanasios Gerasopoulos, Athanasios Koukounaras, Anastasios S. Siomos, Dimitrios Gerasopoulos
Publikováno v:
Horticulturae, Vol 10, Iss 5, p 500 (2024)
Enzymatic browning, occurring on the cut surfaces of many popular fresh-cut fruit and vegetables due to wounding and the activity of endogenous polyphenyloxidase enzymes, is considered as the main reason for their rejection by consumers. In this stud
Externí odkaz:
https://doaj.org/article/c58fb4b552414e15bbfd3467254e1fe8
Autor:
A. Gkikas, A. Gialitaki, I. Binietoglou, E. Marinou, M. Tsichla, N. Siomos, P. Paschou, A. Kampouri, K. A. Voudouri, E. Proestakis, M. Mylonaki, C.-A. Papanikolaou, K. Michailidis, H. Baars, A. G. Straume, D. Balis, A. Papayannis, T. Parrinello, V. Amiridis
Publikováno v:
Atmospheric Measurement Techniques, Vol 16, Pp 1017-1042 (2023)
Since 2018, the Aeolus satellite of the European Space Agency (ESA) has acquired wind HLOS (horizontal line-of-sight) profiles throughout the troposphere and up to the lower stratosphere, filling a critical gap in the Global Observing System (GOS). A
Externí odkaz:
https://doaj.org/article/39994d1ddacf41a8a4a11e5ddae84827